The road to Utopia is the road to Hell. — Communism and socialism are the opiates of the intelligentsia. — The left, in its eternal and futile quest for "equality", is more than willing to abolish liberty and sunder fraternity.

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Macroeconomic Modeling Revisited

Modeling is not science. Take Professor Ray Fair, for example. He teaches macroeconomic theory, econometrics, and macroeconometric models at Yale University. He has been plying his trade since 1968, first at Princeton, then at M.I.T., and (since 1974) at Yale. Those are big-name schools, so I assume that Prof. Fair is a big name in his field.

Well, since 1983 Professor Fair has been forecasting changes in real GDP four quarters ahead. He has made dozens of forecasts based on a model that he has tweaked many times over the years. The current model can be found here. His forecasting track record is here.

How has he done? Here’s how:

1. The mean absolute error of his forecasts is 70 percent; that is, on average his predictions vary by 70 percent from actual rates of growth.

2. The median absolute error of his forecasts is 33 percent.

3. His forecasts are systematically biased: too high when real, four-quarter GDP growth is less than 3 percent; too low when real, four-quarter GDP growth is greater than 3 percent. (See figure 1.)

Given the foregoing, you might think that Fair’s record reflects the persistent use of a model that’s too simple to capture the dynamics of a multi-trillion-dollar economy. But you’d be wrong. The model changes quarterly. This page lists changes only since late 2009; there are links to archives of earlier versions, but those are password-protected.

The theory behind the Rahn Curve is simple — but not simplistic. A relatively small government with powers limited mainly to the protection of citizens and their property is worth more than its cost to taxpayers because it fosters productive economic activity (not to mention liberty). But additional government spending hinders productive activity in many ways, which are discussed in Daniel Mitchell’s paper, “The Impact of Government Spending on Economic Growth.” (I would add to Mitchell’s list the burden of regulatory activity, which grows even when government does not.)

What does the Rahn Curve look like? Mitchell estimates this relationship between government spending and economic growth:

The curve is dashed rather than solid at low values of government spending because it has been decades since the governments of developed nations have spent as little as 20 percent of GDP. But as Mitchell and others note, the combined spending of governments in the U.S. was 10 percent (and less) until the eve of the Great Depression. And it was in the low-spending, laissez-faire era from the end of the Civil War to the early 1900s that the U.S. enjoyed its highest sustained rate of economic growth.

Elsewhere, I estimated the Rahn curve that spans most of the history of the United States. I came up with this relationship (terms modified for simplicity (with a slight cosmetic change in terminology):

Yg = 0.054 -0.066F

To be precise, it’s the annualized rate of growth over the most recent 10-year span (Yg), as a function of F (fraction of GDP spent by governments at all levels) in the preceding 10 years. The relationship is lagged because it takes time for government spending (and related regulatory activities) to wreak their counterproductive effects on economic activity. Also, I include transfer payments (e.g., Social Security) in my measure of F because there’s no essential difference between transfer payments and many other kinds of government spending. They all take money from those who produce and give it to those who don’t (e.g., government employees engaged in paper-shuffling, unproductive social-engineering schemes, and counterproductive regulatory activities).

When F is greater than the amount needed for national defense and domestic justice — no more than 0.1 (10 percent of GDP) — it discourages productive, growth-producing, job-creating activity. And because government spending weighs most heavily on taxpayers with above-average incomes, higher rates of F also discourage saving, which finances growth-producing investments in new businesses, business expansion, and capital (i.e., new and more productive business assets, both physical and intellectual).

I’ve taken a closer look at the post-World War II numbers because of the marked decline in the rate of growth since the end of the war (Figure 2).

Here’s the revised result, which accounts for more variables:

Yg = 0.0275 -0.340F + 0.0773A – 0.000336R – 0.131P

Where,

Yg = real rate of GDP growth in a 10-year span (annualized)

F = fraction of GDP spent by governments at all levels during the preceding 10 years

A = the constant-dollar value of private nonresidential assets (business assets) as a fraction of GDP, averaged over the preceding 10 years

R = average number of Federal Register pages, in thousands, for the preceding 10-year period

P = growth in the CPI-U during the preceding 10 years (annualized).

The r-squared of the equation is 0.74 and the F-value is 1.60E-13. The p-values of the intercept and coefficients are 0.093, 3.98E-08, 4.83E-09, 6.05E-07, and 0.0071. The standard error of the estimate is 0.0049, that is, about half a percentage point.

Here’s how the equation stacks up against actual 10-year rates of real GDP growth:

What does the new equation portend for the next 10 years? Based on the values of F, A, R, and P for 2008-2017, the real rate of growth for the next 10 years will be about 2.0 percent.

There are signs of hope, however. The year-over-year rate of real growth in the four most recent quarters (2017Q4 – 2018Q3) were 2.4, 2.6, 2.9, and 3.0 percent, as against the dismal rates of 1.4, 1.2, 1.5, and 1.8 percent for four quarters of 2016 — Obama’s final year in office. A possible explanation is the election of Donald Trump and the well-founded belief that his tax and regulatory policies would be more business-friendly.

I took the data set that I used to estimate the new equation and made a series of out-of-sample estimates of growth over the next 10 years. I began with the data for 1946-1964 to estimate the growth for 1965-1974. I continued by taking the data for 1946-1965 to estimate the growth for 1966-1975, and so on, until I had estimated the growth for every 10-year period from 1965-1974 through 2008-2017. In other words, like Professor Fair, I updated my model to reflect new data, and I estimated the rate of economic growth in the future. How did I do? Here’s a first look:

FIGURE 5

For ease of comparison, I made the scale of the vertical axis of figure 5 the same as the scale of the vertical axis of figure 2. It’s obvious that my estimate of the Rahn Curve does a much better job of predicting the real rate of GDP growth than does Fair’s model.

Not only that, but my model is less biased:

FIGURE 6

The systematic bias reflected in figure 6 is far weaker than the systematic bias in Fair’s estimates (figure 1).

The moral of the story: It’s futile to build complex models of the economy. They can’t begin to capture the economy’s real complexity, and they’re likely to obscure the important variables — the ones that will determine the future course of economic growth.

A final note: Elsewhere (e.g., here) I’ve disparaged economic aggregates, of which GDP is the apotheosis. And yet I’ve built this post around estimates of GDP. Am I contradicting myself? Not really. There’s a rough consistency in measures of GDP across time, and I’m not pretending that GDP represents anything but an estimate of the monetary value of those products and services to which monetary values can be ascribed.

As a practical matter, then, if you want to know the likely future direction and value of GDP, stick with simple estimation techniques like the one I’ve demonstrated here. Don’t get bogged down in the inconclusive minutiae of a model like Professor Fair’s.

Comments & Correspondence

Now that this blog is in hiatus, I have closed comments on all posts. If you wish to communicate privately, you may e-mail me at the Germanic nickname for Friedrich followed by the last name of the great Austrian economist and Nobel laureate whose first name is Friedrich followed by the 3rd and 4th digits of his birth year followed by the usual typographic symbol followed by the domain and extension for Google’s e-mail service — all run together.

On Liberty and Libertarianism

What is liberty? It is peaceful, willing coexistence and its concomitant: beneficially cooperative behavior.

John Stuart Mill opined that "the only purpose for which power can be rightfully exercised over any member of a civilized community, against his will, is to prevent harm to others." But who determines whether an act is harmful or harmless? Acts deemed harmless by an individual are not harmless if they subvert the societal bonds of trust and self-restraint upon which liberty itself depends.

Which is not to say that all social regimes are regimes of liberty. Liberty requires voice -- the freedom to dissent -- and exit -- the freedom to choose one's neighbors and associates. Voice and exit depend, in turn, on the rule of law under a minimal state.

Liberty, because it is a social phenomenon and not an innate condition of humanity, must be won and preserved by an unflinching defense of a polity that fosters liberty through its norms, and the swift and certain administration of justice within that polity. The governments in and of the United States have long since ceased to foster liberty, but most Americans are captives in their own land and have no choice but to strive for the restoration of liberty, or something closer to it.

Who can restore liberty? Certainly not the self-proclaimed libertarians who are fixated on Mill's empty harm principle and align with the left on social norms. Traditional (i.e., Burkean) conservatism fosters the preservation and adherence of beneficial norms (e.g., the last six of the Ten Commandments). Thus, by necessity, the only true libertarianism is found in traditional conservatism. I am a traditional conservative, which makes me a libertarian -- a true one.

Notes about Usage

“State” (with a capital “S”) refers to one of the United States, and “States” refers to two or more of them. “State” and “States,” thus used, are proper nouns because they refer to a unique entity or entities: one or more of the United States, the union of which, under the terms and conditions stated in the Constitution, is the raison d’être for the nation. I reserve the uncapitalized word “state” for a government, or hierarchy of them, which exerts a monopoly of force within its boundaries.

Marriage, in the Western tradition, predates the state and legitimates the union of one man and one woman. As such, it is an institution that is vital to civil society and therefore to the enjoyment of liberty. The recognition of a more-or-less permanent homosexual pairing as a kind of marriage is both ill-advised and illegitimate. Such an arrangement is therefore a “marriage” (in quotation marks) or, more accurately, a homosexual cohabitation contract (HCC).

The words “liberal”, “progressive”, and their variants are usually enclosed in quotation marks (sneer quotes) because they refer to persons and movements whose statist policies are, in fact, destructive of liberty and progress. I sometimes italicize the words, just to reduce visual clutter.

I have reverted to the British style of punctuating in-line quotations, which I followed 40 years ago when I published a weekly newspaper. The British style is to enclose within quotation marks only (a) the punctuation that appears in quoted text or (b) the title of a work (e.g., a blog post) that is usually placed within quotation marks.

I have reverted because of the confusion and unsightliness caused by the American style. It calls for the placement of periods and commas within quotation marks, even if the periods and commas don’t occur in the quoted material or title. Also, if there is a question mark at the end of quoted material, it replaces the comma or period that might otherwise be placed there.

If I had continued to follow American style, I would have ended a sentence in a recent post with this:

What a hodge-podge. There’s no comma between the first two entries, and the sentence ends with an inappropriate question mark. With two titles ending in question marks, there was no way for me to avoid a series in which a comma is lacking. I could have avoided the sentence-ending question mark by recasting the list, but the items are listed chronologically, which is how they should be read.

This not only eliminates the hodge-podge, but is also more logical and accurate. All items are separated by commas, commas aren’t displaced by question marks, and the declarative sentence ends with a period instead of a question mark.